Modeling Combinatorial Intervention Effects in Transcription Networks
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Modeling Combinatorial Intervention Effects in Transcription Networks. (The Sound of One-Hand Clapping). Achim Tresch Computational Biology Gene Center Munich. The Question. If two hands clap and there is a sound; what is the sound of one hand?. (Japanese Kōan). Kōan

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Modeling Combinatorial Intervention Effects in Transcription Networks

(The Sound of One-Hand Clapping)

Achim TreschComputational Biology

Gene Center Munich


The Question Networks

If two hands clap and there is a sound;

what is the sound of one hand?

(Japanese Kōan)

Kōan

A paradoxical anecdoteor riddle, used in Zen Buddhism to demonstrate the inadequacy of logical reasoning and to provoke enlightenment.


Synthetic Genetic Interactions Networks

How to define “Interaction“ mathematically?

GrowthYB of single manipulation of B

ΔB

GrowthYA of single manipulation of A

Synthetic Genetic Array

ΔA

Growth YABof double manipulation of A and B

ΔA ΔB

modified after Collins, Krogan et al., Nature 2007


Synthetic Genetic Interactions Networks

Phenotype Measurement YBof single perturbation

How to define “Interaction“ mathematically?

ΔB

ΔA

Phenotype Measurement YAof single perturbation

Phenotype Measurement YABof double perturbation

The interaction score SAB is a function of the two single perturbations and the combined perturbation,

ΔA ΔB

SAB= SAB (YA ,YB ,YAB )


Synthetic Genetic Interactions Networks

Common Interaction Scores

Define an expected phenotype of the double perturbation as a function f(YA ,YB ) of the single perturbation phenotypes YA and Yb. The interaction score SAB is then the deviation from the expected phenotype

SAB= YAB - f(YA ,YB )

Common choices for f :f = min(YA ,YB ) (v. Liebig´s minimum rule for plant growth)

f = YA ·YB(chemical equilibrium a + b ↔ ab , [a][b] = [ab])

f = YA + YB (log version of YA ·YB ) f = log2[(2YA - 1)(2YB - 1) + 1](essentially the same as YA + YB )

Results crucially depend on f

Interaction Scores are not very reliable

Mani, Roth et al., PNAS 2007


Synthetic Genetic Interactions Networks

Breakthrough: Combine a set of weak predictors to create a strong predictor (guilt by association = correlation of interaction scores)

Pan, Boeke et al., Cell 2006

Collins, Krogan et al., Nature 2007

Cartoon by Van de Peppel et al, Mol. Cell 2005


Synthetic Genetic Interactions Networks

Take home message: Two components are likely to interact (physically) whenever they have the same interaction partners

Costanzo M, Myers CL, Andrews BJ, Boone C, et al.: Science 2010


Screening for TF interactions Networks

If two hands clap and there is a sound;

what is the sound of one hand?

ΔA

One manipulation

High dimensionalreadout


Genetic interactions from one perturbation Networks

Step 1: Construct a transcription factor - target graph

a) From ChIP binding experiments

Harbison, Fraenkel, Young et al. Nature 2004MacIsaac, Fraenkel et al. BMC Bioinformatics 2006

b) From protein binding arrays, followed by PWM-based predictions

Ansari et al., Nature Methods 2010

Berger, Bulyk et al., Nature Biotech 2006


Genetic interactions from one perturbation Networks

Step 1: Construct a transcription factor - target graph

Intersection size of target sets of TF1 and TF2 can be used alone to assess TF cooperativity. (Beyer, Ideker et al., PlOS Comp. Biol 2006)


Genetic interactions from one perturbation Networks

Step 2: Combine TF-target information and expression data

~2.000 target genes

118 transcription factors

Established Methods for the detection of univariate TF activity :

GSEA (Subramanian, Tamayo PNAS 2005)

Globaltest (Goemann, Bioinformatics 2004)

MGSEA (Bauer, Gagneur, Nucl. Acids Res. 2010)

and many more …

Common Idea: A TF is active if its set of target genes shows significantly altered expression.

To quantify this, various tests are constructed.

Graph obtained from MacIsaac et al. (BMC Bioinformatics 2006)


Genetic interactions from one perturbation Networks

Step 3: Given TF1 and TF2, group genes into 4 interaction classes

TF1

TF1

Binding sites

Synthesis rates during salt stress

TF 1

TF 2

gene 1

TF2

TF2

TF 1 is active

gene 2

TF 2 is active

gene 3

TF 1+2 active

gene 4

time

Antagonistic interaction of TF 1+2


Genetic interactions from one perturbation Networks

Step 3: Given TF1 and TF2, group genes into 4 interaction classes

Binding sites

Synthesis rates during salt stress

TF 1

TF 2

gene 1

TF 1 is inactive

gene 2

TF 2 is inactive

gene 3

TF 1+2 active

gene 4

time

Synergistic interaction of TF1+2


Genetic interactions from one perturbation Networks

Step 4: Use these 4 groups to define an interaction score

For any pair of transcription factors T1 and T2, we perform a logistic regression.

(for all genes g)

Our interaction score for the pair (T1,T2) is then β12.


Genetic interactions from one perturbation Networks

Step 4: Use these 4 groups to define an interaction score

Binding sites

Example:

TF 1

TF 2

gene 1

TF 1 is active

gene 2

TF 2 is active

gene 3

TF 1+2 active

gene 4

time

Antagonistic interaction


Application: Osmotic stress in yeast Networks

Use the guilt by association trick to construct an interaction matrix for all transcription factors using only a two group microarray comparison!

Inclusion criterion: only TFs with >70 targets

„One hand clapping“

Miller, Tresch, Cramer et al., Mol. Syst. Biol. 2010, in revision


Application: Osmotic stress in yeast Networks

Validation with BioGRID database:

Among 84 TFs under consideration (with enough targets), 3486 potential interactions

Exist. Only 97 interactions are recorded.


Application: Osmotic stress in yeast Networks

Validation with BioGRID database:

Single interactions scores don‘t work well

Profile correlations do work


Genetic interactions from one intervention Networks

One hand clapping can be applied to: Microarray data, Pol II ChIP data, nascent RNA data

Application to a similar dataset leads to similar results:

(Mitchell, Pilpel at al. Nature 2009):

3 stress responses:

osmotic stress NaCl, osmotic stress KCl, heat shock


Acknowledgements Networks

Gene Center Munich:

Patrick CramerDietmar MartinBjörn Schwalb

Sebastian Dümcke


My Answer Networks

Two hands clap and there is a sound;

what is the sound of one hand?

It is similar for transcription factors that interact.

Systems Buddhism

Zen Biology


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